python验证特征缩放前后结果

import numpy as np
from sklearn import linear_model
x=[[1],[2],[3],[4],[5]]
y=[100,200,300,400,500]
y2=[]
avg=np.mean(y)
for i in range(len(x)):
    y2.append(y[i]/avg)
clf=linear_model.LinearRegression()
X=[[2]]
clf.fit(x,y)
start=clf.predict(X)
clf.fit(x,y2)
end=clf.predict(X)
print(start)
print(end*avg)

y=[[1],[2],[3],[4],[5]]
x=[[100],[200],[300],[400],[500]]
x2=[[0],[0],[0],[0],[0]]
avg=np.mean(x)
for i in range(len(x)):
    x2[i][0]=x[i][0]/avg
clf=linear_model.LinearRegression()
X=[[100]]
clf.fit(x,y)
start=clf.predict(X)
clf.fit(x2,y)
end=clf.predict(X/avg)
print(start)
print(end)